associate professor of biology
Fields of Interest
Computational biology, non-coding RNA discovery and validation, molecular evolution, RNA and protein structure.
The biological roles of RNA, beyond encoding proteins, have expanded in the last decade to include a diversity of important gene regulatory functions in nearly all living things. At the same time, genome sequencing efforts have produced a wealth of data that can be mined through comparative genomics in order to study the evolution non-coding RNAs (ncRNAs), as well as identify previously unknown non-coding RNAs. We use a combination of computational and experimental tools to both discover new structured non-coding RNAs, as well as examine how these RNAs and their protein partners evolve.
Comparative genomics to discovery novel RNA-protein cis-regulatory interactions and examine their evolution
The largest, and arguably the most important, RNA-protein machine is the ribosome. It is composed of 3 RNA molecules that total nearly 5000 bases and over 50 protein subunits. The coordination of stoichiometric levels of the different protein subunits is accomplished in E. coli through a system of autoregulatory mechanisms where ribosomal proteins bind portions of their own mRNAs to prevent transcription, translation. While these mechanisms are well known in E. coli, they are not always conserved in other bacteria. We use comparative genomics to both understand the evolutionary origins of these RNA/protein complexes, as well as discover previously unidentified ncRNA elements associated with RNA binding proteins.
An important supplement to the bioinformatic description of ncRNAs regulatory elements is the experimental verification that they act as hypothesized. Experiments to verify these interactions include in vivo genetic approaches that demonstrate regulation in the native organism where possible or a surrogate organism. In vitro approaches using purified RNA and protein components are also used to demonstrate direct RNA-protein interaction.
Laboratory Evolution of RNA/protein regulatory complexes
Laboratory evolution is a powerful tool for understanding natural evolution. The ribosomal protein autoregulatory sequences described above provide us with a model system in which to experimentally examine how RNA-protein interactions evolve. In particular, I am intrigued by cases where multiple different RNAs have evolved to bind homologous ribosomal proteins in different organisms. By using laboratory evolution to examine what alternative regulatory systems might be possible, we hope to better understand what factors influence the natural evolution of such regulatory systems.
Fu Y, Deiorio-Haggar K, Soo MW, Meyer MM: Bacterial RNA motif in the 5' UTR of rpsF interacts with an S6:S18 complex. RNA (2014) 20:168-176.
Fu Y, Deiorio-Haggar K, Anthony J, Meyer MM: Most RNAs regulating ribosomal protein biosynthesis in E. coli are narrowly distributed to Gammaproteobacteria. Nucleic Acids Research, 2013.
Miller C, Anthony J, Meyer MM, Marth G: Scribl: An HTML5 Canvas-based graphic library for visualizing genomic data over the web. Bioinformatics 2013, 29:381-383.
Zarringhalam K, Meyer MM, Dotu I, Chuang JH, Clote P: Integrating chemical footprinting data into RNA secondary structure prediction. PLOS ONE 2012, 7:e45160.
Weinberg Z, Perreault P, Meyer MM, Breaker RR: Exceptional Structured Non-coding RNAs Revealed by Bacterial Metagenome Analysis. Nature 2009, 462:656-659.
Meyer MM, Ames TD, Smith DP, Weinberg Z, Schwalbach MS, Giovannoni SJ, Breaker RR: Identification of candidate structured RNAs in the marine organism ‘Candidatus Pelagibacter ubique’. BMC Genomics 2009, 10:26.
Drummond DA, Silberg JJ, Meyer MM, Wilke CO, Arnold FH: On the conservative nature of intragenic recombination. Proc. Natl. Acad. Sci. 2005, 102:5380-5385.